参考：
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:cosmos_qa')
- 说明：
Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
- 许可：无已知许可
- 版本：0.1.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
6963 |
'train' |
25262 |
'validation' |
2985 |
- 特征：
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer0": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer3": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}